Adaptive Network Optimization via Closed-Loop Feedback
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Solution Overview
Problem
Current mobile wireless networks lack self-optimization capabilities to dynamically adapt to changing user demands and environmental conditions due to manual configuration procedures that are tedious and time-consuming, not incorporating closed-loop feedback.
Innovation Solution
An adaptive self-optimizing network system using closed-loop feedback, where a global network operations center generates configuration commands based on operator inputs and key performance indicators, allowing for dynamic adjustments in network configurations, including beam allocations, capacity management, and resource distribution across network access nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration procedures are used to change network access node settings, then network operator control is maintained, but the process becomes tedious and time-consuming
Solution Approach 1:
The network access nodes automatically monitor their own performance metrics (signal strength, interference levels, throughput) and autonomously adjust their configuration parameters (beamforming weights, power levels, antenna patterns) without requiring manual operator intervention. This self-service capability eliminates the tedious manual configuration process while maintaining optimal network performance.
Solution Approach 2:
The system implements closed-loop feedback where network access nodes continuously report performance metrics to a network controller, which then automatically generates and sends configuration commands back to the nodes. This feedback mechanism enables rapid iterative optimization of network parameters, dramatically reducing configuration change time compared to manual procedures.
2Adaptability or versatility
If manual configuration changes are implemented without closed-loop feedback, then operator control is maintained, but self-organization and self-optimization capabilities are lost
Solution Approach 1:
Network access nodes autonomously adapt to changing environmental conditions (obstacles, interference, user mobility) by continuously monitoring their own performance metrics and automatically adjusting their transmission parameters. This self-service capability provides real-time adaptation without requiring manual reconfiguration, enabling the network to respond dynamically to changing conditions.
Solution Approach 2:
The system employs closed-loop feedback where performance metrics (signal-to-interference ratios, throughput measurements, connection quality indicators) are continuously monitored and fed back to the network controller. Based on this feedback, the controller automatically generates optimization commands that adapt network configurations in real-time, providing both adaptability and self-optimization capabilities.
3Productivity
If dynamic configuration changes are made to adapt to changing user locations and loading patterns, then network performance is optimized, but manual procedures become too time-consuming
Solution Approach 1:
Network access nodes automatically detect changes in user distribution and traffic loading patterns through continuous performance monitoring, and autonomously reconfigure their beamforming patterns, power allocation, and resource assignment to optimize network capacity. This self-service capability enables rapid adaptation to changing demand patterns without the delays inherent in manual reconfiguration procedures.
Solution Approach 2:
The system implements real-time feedback loops where network performance metrics (throughput, load balancing indicators, user satisfaction measures) are continuously measured and fed back to the network controller. This feedback enables automated, rapid reconfiguration of network parameters to optimize productivity in response to changing user locations and loading patterns, eliminating the time constraints of manual procedures.
Data Source
AI summary
Systems, methods, and apparatus for an adaptive self-optimizing network using closed-loop feedback are disclosed. A method for sharing network resources comprises receiving, by a network operations center (NOC), access requests for users subscribed to an external network. The method further comprises receiving, by the NOC, a summary of key performance indicators from at least one internal network. Also, the method comprises determining, by the NOC, whether at least one internal network has available resources by analyzing the summary of key performance indicators and user demand from the access requests. Further, the method comprises allowing, by the NOC when the NOC determines that there are available resources, at least some of the users from the external network to connect to at least one internal network according to the available resources.